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# Line of best fit watch

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1. How do I interpret the line of best fit. Say if the points are close to the line of best fit, what does that mean? And if they aren't, what does that mean? Also if the gradient of my line of best fit for a place (lets call Japan) is like -1.532 and another line of best fit for a different place (lets call Canada) is -1.912, what does this conclude if I am measuring distance against noise.
3. (Original post by chickengoujon)
How do I interpret the line of best fit. Say if the points are close to the line of best fit, what does that mean? And if they aren't, what does that mean? Also if the gradient of my line of best fit for a place (lets call Japan) is like -1.532 and another line of best fit for a different place (lets call Canada) is -1.912, what does this conclude if I am measuring distance against noise.
Hard to answer your question without knowing what calculations you've done or the context of the question.
Have you calculated the strength of the correlation (eg product moment correlation coefficient or spearmans rank)? in general if points are closer to your line of best fit you can be more confident in your conclusion that there is linear correlation
Have you calculated a line of best fit or done it by eye? By eye i wouldn't bother comparing two sets of data as the guesses by eye are notoriously inaccurate. If you have calculated it then the mathematicians interpretation of the gradient would be to simply say what you see, e.g. As distance increases by 1 (mile, km, m, cm ?) noise decreases by 1.5 and 1.9 (units) respectively. Mathematicians would not go on to say any more but if you are doing this in the context of some other subject you might go on to offer explanations of why or what it means from insight gained from the two locations.
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Updated: October 10, 2017
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